The Immune Cell Atlas (ICA) is a collaborative consortium of scientists and clinicians with distinct and synergistic expertise in Immunology and Genomics (Benoist, Hacohen, Merad) and Computational Immunology (Regev) with the goal of generating a comprehensive map of all immune cell populations that reside in human tissues at baseline and challenged states. The ICA inherits from and amplifies Immgen, a multi-institutional collaboration of immunologists and computational biologists which used rigorously shared SOPs to generate gene expression profiles of essentially all cell-types in the mouse immune system, and implemented user-friendly online data portals for easy public access that have become a valuable reference. The ICA will be carried out in synergy with a parallel effort in the UK (Oxford and the Wellcome Trust Sanger Institute), giving the project a broader tissue sampling bandwidth and far reaching access to diverse tissue types and disease states. This effort is integrated into the broader Human Cell Atlas Project (HCA), which aims to complete the 150-year-old dream to identify all cell types in the human body. This community resource project will harness the power of single-cell RNA sequencing (scRNA-seq) to generate a unified cartography of human immune cells. To achieve this goal, we will implement rigorous sample acquisition and processing and analytical pipelines to allow the coordinate analysis of immune cells from many locations, and to integrate these datasets for pooled and normalized analysis, such that a cell in any location or condition can be related to all others. Immune cells do not solely reside in the blood, so we will explore lymphoid organs, as well as frontline (gut, lung, skin) and internal (liver, brain, kidney) tissues in which immune cells reside and mount immuno/inflammatory responses. Because the immune system only manifests its potential when challenged, samples from infectious, inflammatory and tumoral lesions will be analyzed in addition to healthy tissues, selected to reveal the states into which immune cells can be coaxed. We will use unsupervised analysis, which avoids relying on pre-determined marker-based classifications of cell populations, to identify stable immune cell subsets and functional continua. Conventional profiling of sorted populations will complement the single-cell profiles, and allow a deeper, more comprehensive dive into the transcriptomes of cell types uncovered by the single-cell analysis. Working with specific Advisory Panels and harnessing community input, we will derive from these data comprehensive tree and genomic maps of immune cell-types and -states, which will be made publicly accessible through a cloud-enabled data platform, a user- friendly online data portal and mobile apps